Analysis of NEO Cryptocurrency Price
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This report provides an analysis of the price of NEO cryptocurrency for a period of one year. It includes descriptive analysis, graphical analysis, correlation analysis, and regression analysis. The study aims to investigate the trend in the prices of NEO cryptocurrency and the relationship between the price and circulation of the cryptocurrency.
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Running Head: NEO CRYPTOCURRENCY
1
ANALYSIS OF THE PRICE OF NEO CRYPTOCURRENCY FOR A PERIOD OF ONE
YEAR (22ND APRIL, 2018 TO 21ST APRIL 2019)
Money and Banking
Name of Student:
Name of Student:
Date:
1
ANALYSIS OF THE PRICE OF NEO CRYPTOCURRENCY FOR A PERIOD OF ONE
YEAR (22ND APRIL, 2018 TO 21ST APRIL 2019)
Money and Banking
Name of Student:
Name of Student:
Date:
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NEO CRYPTOCURRENCY
2
Contents
Introduction.................................................................................................................................................3
Importance of the Study..............................................................................................................................5
Analysis.......................................................................................................................................................6
Descriptive Analysis................................................................................................................................8
Graphical Analysis..................................................................................................................................9
Correlation Analysis..............................................................................................................................11
Regression Analysis..............................................................................................................................11
Conclusion.................................................................................................................................................12
References.................................................................................................................................................14
Appendix...................................................................................................................................................15
Predicted Neo Cryptocurrency Prices....................................................................................................15
Regression Plots....................................................................................................................................24
2
Contents
Introduction.................................................................................................................................................3
Importance of the Study..............................................................................................................................5
Analysis.......................................................................................................................................................6
Descriptive Analysis................................................................................................................................8
Graphical Analysis..................................................................................................................................9
Correlation Analysis..............................................................................................................................11
Regression Analysis..............................................................................................................................11
Conclusion.................................................................................................................................................12
References.................................................................................................................................................14
Appendix...................................................................................................................................................15
Predicted Neo Cryptocurrency Prices....................................................................................................15
Regression Plots....................................................................................................................................24
NEO CRYPTOCURRENCY
3
Introduction
A cryptocurrency is a digital medium that is used for the exchange of goods and services
over the internet (Blakstad, Sofie, Allen, & Robert, 2018). There are several cryptocurrencies
that exists over the internet. The cryptocurrencies have universal prices that are accessible
publicly to everyone. The value of a cryptocurrency is measured by its current price. Therefore,
it is possible to investigate the price movement of any cryptocurrency over any given time
periods (Furneaux & Nick, 2018).
The price or value of a cryptocurrency changes like the prices of shares in the market.
The price of a cryptocurrency is determined by forces of the market; demand and supply.
Therefore, the prices of cryptocurrencies are as volatile as that of a stock; the prices of
cryptocurrencies change every second (Catalini & Christin, 2018). However, it is possible to get
a daily price of a cryptocurrency. The daily price of a cryptocurrency can be obtained by getting
the average of the lowest and the highest price in a day (Hattori, Takahiro, Ishida, & Ryo, 2018).
The daily lowest and highest cryptocurrency prices are available in the internet.
The analysis of in this report focused on neo cryptocurrency. The neo cryptocurrency was
formerly known as Ant shares. The aim of neo cryptocurrency is to build a ‘smart economy’.
Neo cryptocurrency aims to build a ‘smart economy’ by incorporating digital assets, digital
identities and enhancing smart contracts. Neo cryptocurrency was developed by Onchain DNA,
Neo's dual-token ecosystem can be used for creating Apps and ICOs. Neo cryptocurrency’s
delegated Byzantine Fault Tolerance (dBFT) consensus algorithm is purportedly faster than the
POW used by Ethereum and Bitcoin.
3
Introduction
A cryptocurrency is a digital medium that is used for the exchange of goods and services
over the internet (Blakstad, Sofie, Allen, & Robert, 2018). There are several cryptocurrencies
that exists over the internet. The cryptocurrencies have universal prices that are accessible
publicly to everyone. The value of a cryptocurrency is measured by its current price. Therefore,
it is possible to investigate the price movement of any cryptocurrency over any given time
periods (Furneaux & Nick, 2018).
The price or value of a cryptocurrency changes like the prices of shares in the market.
The price of a cryptocurrency is determined by forces of the market; demand and supply.
Therefore, the prices of cryptocurrencies are as volatile as that of a stock; the prices of
cryptocurrencies change every second (Catalini & Christin, 2018). However, it is possible to get
a daily price of a cryptocurrency. The daily price of a cryptocurrency can be obtained by getting
the average of the lowest and the highest price in a day (Hattori, Takahiro, Ishida, & Ryo, 2018).
The daily lowest and highest cryptocurrency prices are available in the internet.
The analysis of in this report focused on neo cryptocurrency. The neo cryptocurrency was
formerly known as Ant shares. The aim of neo cryptocurrency is to build a ‘smart economy’.
Neo cryptocurrency aims to build a ‘smart economy’ by incorporating digital assets, digital
identities and enhancing smart contracts. Neo cryptocurrency was developed by Onchain DNA,
Neo's dual-token ecosystem can be used for creating Apps and ICOs. Neo cryptocurrency’s
delegated Byzantine Fault Tolerance (dBFT) consensus algorithm is purportedly faster than the
POW used by Ethereum and Bitcoin.
NEO CRYPTOCURRENCY
4
The purpose of this report was to provide the analysis of the price of Neo currency for the
last one year. The specific objectives of this report were: To investigate the trend in the prices of
neo cryptocurrency over the last one year; to investigate whether prices are getting high or
getting low, to develop a model that can be used to predict the prices of neo cryptocurrency and
investigate the relationship between the prices of neo cryptocurrency and the circulation of neo
cryptocurrency.
The data set that was used for analysis was collected from the website of the coin market
cap. The dataset consisted of a 365 data points representing one year period (365 days). The
period of the data set is time between 22nd April, 2018 and 21st April, 2019. The data consisted of
the prices of neo cryptocurrency (the daily opening and closing prices, the daily lowest price and
the daily highest price), the volume of sale and the circulation.
The study was completed by testing some hypothesis. Hypothesis is a statement or an
assertion about a subject matter (Vetter & Thomas, 2017). The truth value of a hypothesis can be
determined by testing the hypothesis (Han & Peisong, 2014). A hypothesis testing process start
by the statement of the hypotheses to be tested. Hypothesis is fully tested when both the null and
the alternative hypotheses are tested (Saez-Castillo & Conde-Sanchez, 2013). An alternative
hypothesis is the claim of the researcher. An alternative hypothesis is stated positively (Han &
Peisong, 2014). An alternative hypothesis states that there is a relationship between the variables.
On the other hand, a null hypothesis is stated negatively. A null hypothesis states that
there is no relationship between the variables. A null hypothesis is denoted by H0 while an
alternative hypothesis is denoted by H1. The following hypothesis were tested:
4
The purpose of this report was to provide the analysis of the price of Neo currency for the
last one year. The specific objectives of this report were: To investigate the trend in the prices of
neo cryptocurrency over the last one year; to investigate whether prices are getting high or
getting low, to develop a model that can be used to predict the prices of neo cryptocurrency and
investigate the relationship between the prices of neo cryptocurrency and the circulation of neo
cryptocurrency.
The data set that was used for analysis was collected from the website of the coin market
cap. The dataset consisted of a 365 data points representing one year period (365 days). The
period of the data set is time between 22nd April, 2018 and 21st April, 2019. The data consisted of
the prices of neo cryptocurrency (the daily opening and closing prices, the daily lowest price and
the daily highest price), the volume of sale and the circulation.
The study was completed by testing some hypothesis. Hypothesis is a statement or an
assertion about a subject matter (Vetter & Thomas, 2017). The truth value of a hypothesis can be
determined by testing the hypothesis (Han & Peisong, 2014). A hypothesis testing process start
by the statement of the hypotheses to be tested. Hypothesis is fully tested when both the null and
the alternative hypotheses are tested (Saez-Castillo & Conde-Sanchez, 2013). An alternative
hypothesis is the claim of the researcher. An alternative hypothesis is stated positively (Han &
Peisong, 2014). An alternative hypothesis states that there is a relationship between the variables.
On the other hand, a null hypothesis is stated negatively. A null hypothesis states that
there is no relationship between the variables. A null hypothesis is denoted by H0 while an
alternative hypothesis is denoted by H1. The following hypothesis were tested:
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NEO CRYPTOCURRENCY
5
H0: There is no relationship between the price of a neo cryptocurrency and the circulation
of cryptocurrency.
H1: There is a relationship between the price of a neo cryptocurrency and the circulation
of cryptocurrency.
H0: The price of neo cryptocurrency cannot be determined by volume of new currency
and the amount of new currency in circulation.
H1: The price of neo cryptocurrency can be determined by volume of new currency and
the amount of new currency in circulation.
Importance of the Study
The study is significant to several stakeholders. The findings and recommendations of
this study are significant to the management of neo cryptocurrency, business analysist, investors
in cryptocurrency, the general public, the researchers and academicians in the business filed and
the governments of different countries.
The findings of this study are important to the management of neo cryptocurrency. The
management can use the insights and findings of this study to improve their decision making
process. The management can make more specific decisions that can help them to improve the
value of the currency and make it more preferable to investors.
The individuals working as business analyst will find the insights from this report very
useful to them. The analyst can use the findings and insights from this study to improve their
decision making process. The business analysist can also use the findings and the insights to
5
H0: There is no relationship between the price of a neo cryptocurrency and the circulation
of cryptocurrency.
H1: There is a relationship between the price of a neo cryptocurrency and the circulation
of cryptocurrency.
H0: The price of neo cryptocurrency cannot be determined by volume of new currency
and the amount of new currency in circulation.
H1: The price of neo cryptocurrency can be determined by volume of new currency and
the amount of new currency in circulation.
Importance of the Study
The study is significant to several stakeholders. The findings and recommendations of
this study are significant to the management of neo cryptocurrency, business analysist, investors
in cryptocurrency, the general public, the researchers and academicians in the business filed and
the governments of different countries.
The findings of this study are important to the management of neo cryptocurrency. The
management can use the insights and findings of this study to improve their decision making
process. The management can make more specific decisions that can help them to improve the
value of the currency and make it more preferable to investors.
The individuals working as business analyst will find the insights from this report very
useful to them. The analyst can use the findings and insights from this study to improve their
decision making process. The business analysist can also use the findings and the insights to
NEO CRYPTOCURRENCY
6
advice their clients and companies in a more appropriately. Therefore, the business analysts can
rely on this report as a tool for aiding their investment decision process.
The investors in cryptocurrency will find this report very useful to them. The investors
can use the findings and insights from this report as a benchmark to compare neo cryptocurrency
and other cryptocurrencies. Therefore, the investors can use this report to improve their decision
making process before they invest in the cryptocurrency.
The report is also important to the researchers and academicians in the field of business.
The researchers and academicians can use the report as a reference material in their studies.
Moreover, the researchers and academicians can use the recommendations made on this report to
form the basis of their research. Therefore, the report will act a basis for further studies in the
same field or on the same subject matter.
Analysis
The analysis section presents the techniques that were used to get the meaning out of the
data and achieve the objectives of the study. The first section of the analysis are the preliminary
analyses. A preliminary analyses are done to investigate the characteristics or features of the data
set/ variables of the data set (Saez-Castillo & Conde-Sanchez, 2013). The preliminary analyses
that were conducted include the descriptive statistics and the graphical analysis (Girasa &
Rosario, 2018).
A descriptive analysis is conducted to investigate the summary statistics. The summary
statistics include the measures of central tendency, the measures of dispersion and the measures
of spread (Saez-Castillo & Conde-Sanchez, 2013). Therefore, a descriptive analysis provides the
6
advice their clients and companies in a more appropriately. Therefore, the business analysts can
rely on this report as a tool for aiding their investment decision process.
The investors in cryptocurrency will find this report very useful to them. The investors
can use the findings and insights from this report as a benchmark to compare neo cryptocurrency
and other cryptocurrencies. Therefore, the investors can use this report to improve their decision
making process before they invest in the cryptocurrency.
The report is also important to the researchers and academicians in the field of business.
The researchers and academicians can use the report as a reference material in their studies.
Moreover, the researchers and academicians can use the recommendations made on this report to
form the basis of their research. Therefore, the report will act a basis for further studies in the
same field or on the same subject matter.
Analysis
The analysis section presents the techniques that were used to get the meaning out of the
data and achieve the objectives of the study. The first section of the analysis are the preliminary
analyses. A preliminary analyses are done to investigate the characteristics or features of the data
set/ variables of the data set (Saez-Castillo & Conde-Sanchez, 2013). The preliminary analyses
that were conducted include the descriptive statistics and the graphical analysis (Girasa &
Rosario, 2018).
A descriptive analysis is conducted to investigate the summary statistics. The summary
statistics include the measures of central tendency, the measures of dispersion and the measures
of spread (Saez-Castillo & Conde-Sanchez, 2013). Therefore, a descriptive analysis provides the
NEO CRYPTOCURRENCY
7
features like the mean, the variance, the standard deviation, the mode, the maximum value, the
minimum value, the skewness and kurtosis (Richard, 2009).
A graphical analysis is a way of providing the pictorial display of the observations. A
graphical representation was used in the report to provide a picture of how the prices and the
other variables of neo cryptocurrency have behaved over the past one year. A line graph was
used to represent the daily prices of neo cryptocurrency over the past one year. The line graph
help in obtaining the trend of the daily prices over the past one year. The trend help in
determining whether the prices have going up or going down over the past one year.
Correlation analysis was used to test hypothesis 1 that there is no relationship between
the price of a neo cryptocurrency and the circulation of cryptocurrency versus the alternative
hypothesis that there is a relationship between the price of a neo cryptocurrency and the
circulation of cryptocurrency. Correlation analysis is a statistical technique that is used to
investigate the strength and the nature of the relationship that exists between variables (Vetter &
Thomas, 2017). The strength and nature of the relationship between variables can be determined
by the correlation coefficient between the variables (Vetter & Thomas, 2017).
A correlation coefficient ranges between 1 and -1. A correlation coefficient of 1 is a
perfect positive relationship while a correlation coefficient of -1 is a perfect negative correlation
(Vetter & Thomas, 2017). A correlation coefficient with a value in the range of 0 and 0.5 is a
weak positive relationship while a correlation coefficient of a value in the range of 0.5 and 1 is a
strong positive relationship (Vetter & Thomas, 2017). On the other hand, a correlation
coefficient of the value between 0 and -0.5 is a weak negative correlation while a correlation
7
features like the mean, the variance, the standard deviation, the mode, the maximum value, the
minimum value, the skewness and kurtosis (Richard, 2009).
A graphical analysis is a way of providing the pictorial display of the observations. A
graphical representation was used in the report to provide a picture of how the prices and the
other variables of neo cryptocurrency have behaved over the past one year. A line graph was
used to represent the daily prices of neo cryptocurrency over the past one year. The line graph
help in obtaining the trend of the daily prices over the past one year. The trend help in
determining whether the prices have going up or going down over the past one year.
Correlation analysis was used to test hypothesis 1 that there is no relationship between
the price of a neo cryptocurrency and the circulation of cryptocurrency versus the alternative
hypothesis that there is a relationship between the price of a neo cryptocurrency and the
circulation of cryptocurrency. Correlation analysis is a statistical technique that is used to
investigate the strength and the nature of the relationship that exists between variables (Vetter &
Thomas, 2017). The strength and nature of the relationship between variables can be determined
by the correlation coefficient between the variables (Vetter & Thomas, 2017).
A correlation coefficient ranges between 1 and -1. A correlation coefficient of 1 is a
perfect positive relationship while a correlation coefficient of -1 is a perfect negative correlation
(Vetter & Thomas, 2017). A correlation coefficient with a value in the range of 0 and 0.5 is a
weak positive relationship while a correlation coefficient of a value in the range of 0.5 and 1 is a
strong positive relationship (Vetter & Thomas, 2017). On the other hand, a correlation
coefficient of the value between 0 and -0.5 is a weak negative correlation while a correlation
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NEO CRYPTOCURRENCY
8
coefficient with a value in the range of 0.5 and -1 is a strong negative relationship (Vetter &
Thomas, 2017).
Regression analysis was used to test hypothesis 2. Regression analysis was to test the null
hypothesis that the price of neo cryptocurrency cannot be determined by volume of new currency
and the amount of new currency in circulation versus the alternative hypothesis that the price of
neo cryptocurrency can be determined by volume of new currency and the amount of new
currency in circulation. Regression analysis is a statistical technique that is used to predict one
variable (dependent variable) using two or more variables (independent variables) (Vetter &
Thomas, 2017). The output of regression analysis provides the specification of the model that
can be used for prediction.
Descriptive Analysis
The descriptive analysis below demonstrates that the average daily prices for the past one
year is $23.07, the average volume was $150501499.75 and the average circulation was
1494712196.83. The maximum price of neo cryptocurrency was $88.81 while the minimum
price was $5.61 indicating that the daily price was highly volatile during the one year period.
Volume Circulation Daily
Price
Mean 150501499.75 1494712196.83 23.07
Standard Error 4734187.92 67323938.75 1.04
Median 128178000.00 1058902000.00 16.48
Standard Deviation 90446533.22 1286222043.86 19.83
Sample Variance 8180575371629980.00 1654367146119260000.00 393.04
Kurtosis 6.25 1.83 1.74
Skewness 1.96 1.60 1.58
Range 669354566.00 5552491001.00 83.21
Minimum 44633900.00 367175999.00 5.61
Maximum 713988466.00 5919667000.00 88.81
Sum 54933047410.00 545569951844.00 8419.97
8
coefficient with a value in the range of 0.5 and -1 is a strong negative relationship (Vetter &
Thomas, 2017).
Regression analysis was used to test hypothesis 2. Regression analysis was to test the null
hypothesis that the price of neo cryptocurrency cannot be determined by volume of new currency
and the amount of new currency in circulation versus the alternative hypothesis that the price of
neo cryptocurrency can be determined by volume of new currency and the amount of new
currency in circulation. Regression analysis is a statistical technique that is used to predict one
variable (dependent variable) using two or more variables (independent variables) (Vetter &
Thomas, 2017). The output of regression analysis provides the specification of the model that
can be used for prediction.
Descriptive Analysis
The descriptive analysis below demonstrates that the average daily prices for the past one
year is $23.07, the average volume was $150501499.75 and the average circulation was
1494712196.83. The maximum price of neo cryptocurrency was $88.81 while the minimum
price was $5.61 indicating that the daily price was highly volatile during the one year period.
Volume Circulation Daily
Price
Mean 150501499.75 1494712196.83 23.07
Standard Error 4734187.92 67323938.75 1.04
Median 128178000.00 1058902000.00 16.48
Standard Deviation 90446533.22 1286222043.86 19.83
Sample Variance 8180575371629980.00 1654367146119260000.00 393.04
Kurtosis 6.25 1.83 1.74
Skewness 1.96 1.60 1.58
Range 669354566.00 5552491001.00 83.21
Minimum 44633900.00 367175999.00 5.61
Maximum 713988466.00 5919667000.00 88.81
Sum 54933047410.00 545569951844.00 8419.97
NEO CRYPTOCURRENCY
9
Count 365.00 365.00 365.00
Graphical Analysis
The graph below is a line graph of the daily prices of neo cryptocurrency over the past
one year. The trend line indicates that the prices experienced a consistent fall over the past one
year.
22/Apr/18
11/May/18
30/May/18
18/Jun/18
7/Jul/18
26/Jul/18
14/Aug/18
2/Sep/18
21/Sep/18
10/Oct/18
29/Oct/18
17/Nov/18
6/Dec/18
25/Dec/18
13/Jan/19
1/Feb/19
20/Feb/19
11/Mar/19
30/Mar/19
18/Apr/19
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
100.00
A Line of Daily Price Neo Cryptocurrency
for the last 1 Year
Daily Price Linear (Daily Price)
Daily Price
Day
Daily Price
The line graph below represents the daily volume of neo cryptocurrency over the past one
year. The trend line demonstrates that the volume of neo cryptocurrency have experienced a
consistent downfall over the past one year.
9
Count 365.00 365.00 365.00
Graphical Analysis
The graph below is a line graph of the daily prices of neo cryptocurrency over the past
one year. The trend line indicates that the prices experienced a consistent fall over the past one
year.
22/Apr/18
11/May/18
30/May/18
18/Jun/18
7/Jul/18
26/Jul/18
14/Aug/18
2/Sep/18
21/Sep/18
10/Oct/18
29/Oct/18
17/Nov/18
6/Dec/18
25/Dec/18
13/Jan/19
1/Feb/19
20/Feb/19
11/Mar/19
30/Mar/19
18/Apr/19
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
100.00
A Line of Daily Price Neo Cryptocurrency
for the last 1 Year
Daily Price Linear (Daily Price)
Daily Price
Day
Daily Price
The line graph below represents the daily volume of neo cryptocurrency over the past one
year. The trend line demonstrates that the volume of neo cryptocurrency have experienced a
consistent downfall over the past one year.
NEO CRYPTOCURRENCY
10
Date 14-Jan-19 8-Oct-18 2-Jul-18
0.00
100000000.00
200000000.00
300000000.00
400000000.00
500000000.00
600000000.00
700000000.00
800000000.00
A Line Graph of Daily Volume of Neo
Crypyocurrency for the last one Year
Volume
Linear (Volume)
Day
Volume
The graph below is a line graph of neo circulation over the past one year. The trend of
daily circulation demonstrate that there has been a consistent downfall in the circulation of neo
cryptocurrency over the past one year.
22/Apr/18
15/Jun/18
8/Aug/18
1/Oct/18
24/Nov/18
17/Jan/19
12/Mar/19
0.00
1000000000.00
2000000000.00
3000000000.00
4000000000.00
5000000000.00
6000000000.00
7000000000.00
A Line Graph of Circulationof Neo
Crypyocurrency for the last one Year
Circulation
Linear (Circulation)
Day
Amount in Circulation
10
Date 14-Jan-19 8-Oct-18 2-Jul-18
0.00
100000000.00
200000000.00
300000000.00
400000000.00
500000000.00
600000000.00
700000000.00
800000000.00
A Line Graph of Daily Volume of Neo
Crypyocurrency for the last one Year
Volume
Linear (Volume)
Day
Volume
The graph below is a line graph of neo circulation over the past one year. The trend of
daily circulation demonstrate that there has been a consistent downfall in the circulation of neo
cryptocurrency over the past one year.
22/Apr/18
15/Jun/18
8/Aug/18
1/Oct/18
24/Nov/18
17/Jan/19
12/Mar/19
0.00
1000000000.00
2000000000.00
3000000000.00
4000000000.00
5000000000.00
6000000000.00
7000000000.00
A Line Graph of Circulationof Neo
Crypyocurrency for the last one Year
Circulation
Linear (Circulation)
Day
Amount in Circulation
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NEO CRYPTOCURRENCY
11
Correlation Analysis
Correlation analysis was used investigate whether there is a relationship between the
price and circulation of neo cryptocurrency. The results demonstrate that the correlation
coefficient between circulation and price is 0.9989493. The correlation coefficient is a strong
positive correlation or relationship. The nature of the relationship implies that an increase in the
value of circulation by 1 will cause a corresponding increase in the price of neo cryptocurrency
by 0. 9989493.
Correlation analysis was used to test hypothesis 1. Since the correlation coefficient is not
zero; it implies that there is a relationship hence we reject the null hypothesis.
Volume Circulation Daily Price
Volume 1
Circulation -0.1917 1
Daily Price -0.19518 0.998949378 1
Regression Analysis
Regression analysis was to build a model that can be used to predict the prices of neo
cryptocurrency. The table below shows the model summary. From the model summary, it is clear
that the regression coefficient is 0.999554043, hence we reject null hypothesis 2. The value of R
square is 0.999108284 meaning that the model explains 99.91082% of the population. Therefore,
the regression model is a perfect model.
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.999554043
R Square 0.999108284
Adjusted R Square 0.996351007
Standard Error 0.910269861
11
Correlation Analysis
Correlation analysis was used investigate whether there is a relationship between the
price and circulation of neo cryptocurrency. The results demonstrate that the correlation
coefficient between circulation and price is 0.9989493. The correlation coefficient is a strong
positive correlation or relationship. The nature of the relationship implies that an increase in the
value of circulation by 1 will cause a corresponding increase in the price of neo cryptocurrency
by 0. 9989493.
Correlation analysis was used to test hypothesis 1. Since the correlation coefficient is not
zero; it implies that there is a relationship hence we reject the null hypothesis.
Volume Circulation Daily Price
Volume 1
Circulation -0.1917 1
Daily Price -0.19518 0.998949378 1
Regression Analysis
Regression analysis was to build a model that can be used to predict the prices of neo
cryptocurrency. The table below shows the model summary. From the model summary, it is clear
that the regression coefficient is 0.999554043, hence we reject null hypothesis 2. The value of R
square is 0.999108284 meaning that the model explains 99.91082% of the population. Therefore,
the regression model is a perfect model.
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.999554043
R Square 0.999108284
Adjusted R Square 0.996351007
Standard Error 0.910269861
NEO CRYPTOCURRENCY
12
Observations 365
The ANOVA table below indicates whether there was a significant difference in the
average values of daily neo price, volume and circulation. The value of significance is 0 which is
less than the level of significance (0.05). The significance value demonstrate that there was
indeed a significant difference in the average values of the three variables (price, volume and
circulation).
ANOVA
do SS MS F Significance
F
Regression 2 337002.4883 168501.2 203358.7 0
Residual 363 300.7786131 0.828591
Total 365 337303.2669
The table below provides the model specification. The coefficients were used to build a
model for predicting the daily prices of neo cryptocurrency. The model is given by:
Daily Price= -1.3322E-10 (Volume) 1.5425E-08 (Circulation)
Some of the predicted values for a period of 1 year are available in the appendix. The regression
graphs are also available in the appendix.
Coeffici
ents
Standard
Error
t Stat P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Interce
pt
0
Volum
e
-
1.3322E
-10
3.34997E-
10
-
0.397
67
0.691
104
-7.9E-
10
5.26E-
10
-7.9E-10 5.26E-10
Circula
tion
1.5425E
-08
2.98359E-
11
516.9
959
0 1.54E-
08
1.55E-
08
1.54E-08 1.55E-08
12
Observations 365
The ANOVA table below indicates whether there was a significant difference in the
average values of daily neo price, volume and circulation. The value of significance is 0 which is
less than the level of significance (0.05). The significance value demonstrate that there was
indeed a significant difference in the average values of the three variables (price, volume and
circulation).
ANOVA
do SS MS F Significance
F
Regression 2 337002.4883 168501.2 203358.7 0
Residual 363 300.7786131 0.828591
Total 365 337303.2669
The table below provides the model specification. The coefficients were used to build a
model for predicting the daily prices of neo cryptocurrency. The model is given by:
Daily Price= -1.3322E-10 (Volume) 1.5425E-08 (Circulation)
Some of the predicted values for a period of 1 year are available in the appendix. The regression
graphs are also available in the appendix.
Coeffici
ents
Standard
Error
t Stat P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Interce
pt
0
Volum
e
-
1.3322E
-10
3.34997E-
10
-
0.397
67
0.691
104
-7.9E-
10
5.26E-
10
-7.9E-10 5.26E-10
Circula
tion
1.5425E
-08
2.98359E-
11
516.9
959
0 1.54E-
08
1.55E-
08
1.54E-08 1.55E-08
NEO CRYPTOCURRENCY
13
Conclusion
The purpose of this report was to provide the analysis of the price of Neo currency for the
last one year. The specific objectives of this report were: To investigate the trend in the prices of
neo cryptocurrency over the last one year; to investigate whether prices are getting high or
getting low, to develop a model that can be used to predict the prices of neo cryptocurrency and
investigate the relationship between the prices of neo cryptocurrency and the circulation of neo
cryptocurrency.
The results demonstrates that the prices of neo cryptocurrency are getting low for the past
one year. The prices are falling due to the low demand of the cryptocurrencies (Chamaillard, Ari,
& Chris, 2010). The demand of cryptocurrencies are continuously decreasing due to the fact the
cryptocurrencies are highly expensive. Similarly, there is little trust in the cryptocurrencies
(Chamaillard, Ari, & Chris, 2010).
The results demonstrate that there is a relationship between circulation and the daily price
of neo cryptocurrencies. The relationship is such that an increase in circulation causes an
increase in the daily prices of neo cryptocurrency.
The price of neo cryptocurrency can be predicted using the model:
Daily Price= -1.3322E-10 (Volume) 1.5425E-08 (Circulation)
The model implies that given the daily volume of neo cryptocurrency and the daily
circulation of neo cryptocurrency, the daily prices of neo cryptocurrency can be determined
using the above model.
13
Conclusion
The purpose of this report was to provide the analysis of the price of Neo currency for the
last one year. The specific objectives of this report were: To investigate the trend in the prices of
neo cryptocurrency over the last one year; to investigate whether prices are getting high or
getting low, to develop a model that can be used to predict the prices of neo cryptocurrency and
investigate the relationship between the prices of neo cryptocurrency and the circulation of neo
cryptocurrency.
The results demonstrates that the prices of neo cryptocurrency are getting low for the past
one year. The prices are falling due to the low demand of the cryptocurrencies (Chamaillard, Ari,
& Chris, 2010). The demand of cryptocurrencies are continuously decreasing due to the fact the
cryptocurrencies are highly expensive. Similarly, there is little trust in the cryptocurrencies
(Chamaillard, Ari, & Chris, 2010).
The results demonstrate that there is a relationship between circulation and the daily price
of neo cryptocurrencies. The relationship is such that an increase in circulation causes an
increase in the daily prices of neo cryptocurrency.
The price of neo cryptocurrency can be predicted using the model:
Daily Price= -1.3322E-10 (Volume) 1.5425E-08 (Circulation)
The model implies that given the daily volume of neo cryptocurrency and the daily
circulation of neo cryptocurrency, the daily prices of neo cryptocurrency can be determined
using the above model.
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NEO CRYPTOCURRENCY
14
References
Blakstad, Sofie, Allen, & Robert. (2018). FinTech Revolution || Central Bank Digital Currencies
and Cryptocurrencies. The Journal of FinTech Revolution, 5.
Catalini, & Christin. (2018). Blockchain Technology and Cryptocurrencies: Implications for the
Digital Economy, Cybersecurity, and Government. Georgetown Journal of International
Affairs, 6-12.
Chamaillard, K., Ari, T. F., & Chris, D. (2010). Coherency matrix description for statistical
linear regression of Stokes parameters in rough small-particle scattering. The Journal of
Optics Communications, 5.
Furneaux, & Nick. (2018). Investigating Cryptocurrencies (Understanding, Extracting, and
Analyzing Blockchain Evidence) || Detecting the Use of Cryptocurrencies. The Journal
of Blockchains, 5-9.
Girasa, & Rosario. (2018). Regulation of Cryptocurrencies and Blockchain Technologies ||. The
Journal of Finetch, 3-9.
Han, & Peisong. (2014). Multiply Robust Estimation in Regression Analysis With Missing Data.
The Journal of Journal of the American Statistical Association, 4.
Hattori, Takahiro, Ishida, & Ryo. (2018). Do Investors Arbitrage in the Cryptocurrency Market?
Evidence from the Bitcoin Futures Market. SSRN Electronic Journal, 6.
Richard, P. H. (2009). Applied Regression Analysis and Generalized Linear Models. The journal
of Technometrics, 3-10.
Saez-Castillo, A. J., & Conde-Sanchez, A. (2013). A hyper-Poisson regression model for
overdispersed and underdispersed count data. The Journal of Computational Statistics &
Data Analysis, 5.
Vetter, & Thomas, R. (2017). Descriptive Statistics. The Journal of Anesthesia & Analgesia, 2-
10.
14
References
Blakstad, Sofie, Allen, & Robert. (2018). FinTech Revolution || Central Bank Digital Currencies
and Cryptocurrencies. The Journal of FinTech Revolution, 5.
Catalini, & Christin. (2018). Blockchain Technology and Cryptocurrencies: Implications for the
Digital Economy, Cybersecurity, and Government. Georgetown Journal of International
Affairs, 6-12.
Chamaillard, K., Ari, T. F., & Chris, D. (2010). Coherency matrix description for statistical
linear regression of Stokes parameters in rough small-particle scattering. The Journal of
Optics Communications, 5.
Furneaux, & Nick. (2018). Investigating Cryptocurrencies (Understanding, Extracting, and
Analyzing Blockchain Evidence) || Detecting the Use of Cryptocurrencies. The Journal
of Blockchains, 5-9.
Girasa, & Rosario. (2018). Regulation of Cryptocurrencies and Blockchain Technologies ||. The
Journal of Finetch, 3-9.
Han, & Peisong. (2014). Multiply Robust Estimation in Regression Analysis With Missing Data.
The Journal of Journal of the American Statistical Association, 4.
Hattori, Takahiro, Ishida, & Ryo. (2018). Do Investors Arbitrage in the Cryptocurrency Market?
Evidence from the Bitcoin Futures Market. SSRN Electronic Journal, 6.
Richard, P. H. (2009). Applied Regression Analysis and Generalized Linear Models. The journal
of Technometrics, 3-10.
Saez-Castillo, A. J., & Conde-Sanchez, A. (2013). A hyper-Poisson regression model for
overdispersed and underdispersed count data. The Journal of Computational Statistics &
Data Analysis, 5.
Vetter, & Thomas, R. (2017). Descriptive Statistics. The Journal of Anesthesia & Analgesia, 2-
10.
NEO CRYPTOCURRENCY
15
Appendix
Predicted Neo Cryptocurrency Prices
RESIDUAL OUTPUT
Observation Predicted Daily Price Residuals
1 10.54234557 0.107654428
2 10.94701915 0.057980847
3 11.09902431 0.000975691
4 11.26712029 -0.082120293
5 11.00566865 0.004331348
6 10.96409655 -0.084096552
7 10.72252041 0.272479595
8 11.30017243 -0.200172434
9 11.11905754 0.070942463
10 11.30856378 -0.153563785
11 11.23163001 0.358369994
12 12.47441802 -0.014418019
13 12.19250291 0.147497094
14 12.68923041 0.025769595
15 12.8946094 0.085390596
16 13.08388627 0.141113733
17 13.5303184 -0.290318399
18 12.79789259 0.01210741
19 12.08794937 0.447050629
20 11.48053036 -0.690530365
21 9.9869745 -0.0469745
22 9.945629718 -0.150629718
23 9.831568074 0.158431926
24 9.792400252 -0.277400252
25 9.28067823 0.03432177
26 9.385654259 -0.185654259
27 8.967936461 -0.067936461
28 8.991728532 0.123271468
29 9.173581142 0.096418858
30 9.408169866 -0.103169866
31 9.218613962 -0.018613962
32 9.020107546 0.154892454
33 9.378373173 -0.133373173
34 9.295271177 -0.060271177
35 9.20075126 0.05924874
15
Appendix
Predicted Neo Cryptocurrency Prices
RESIDUAL OUTPUT
Observation Predicted Daily Price Residuals
1 10.54234557 0.107654428
2 10.94701915 0.057980847
3 11.09902431 0.000975691
4 11.26712029 -0.082120293
5 11.00566865 0.004331348
6 10.96409655 -0.084096552
7 10.72252041 0.272479595
8 11.30017243 -0.200172434
9 11.11905754 0.070942463
10 11.30856378 -0.153563785
11 11.23163001 0.358369994
12 12.47441802 -0.014418019
13 12.19250291 0.147497094
14 12.68923041 0.025769595
15 12.8946094 0.085390596
16 13.08388627 0.141113733
17 13.5303184 -0.290318399
18 12.79789259 0.01210741
19 12.08794937 0.447050629
20 11.48053036 -0.690530365
21 9.9869745 -0.0469745
22 9.945629718 -0.150629718
23 9.831568074 0.158431926
24 9.792400252 -0.277400252
25 9.28067823 0.03432177
26 9.385654259 -0.185654259
27 8.967936461 -0.067936461
28 8.991728532 0.123271468
29 9.173581142 0.096418858
30 9.408169866 -0.103169866
31 9.218613962 -0.018613962
32 9.020107546 0.154892454
33 9.378373173 -0.133373173
34 9.295271177 -0.060271177
35 9.20075126 0.05924874
NEO CRYPTOCURRENCY
16
36 9.276155327 0.123844673
37 9.508305001 0.026694999
38 9.316284543 -0.016284543
39 9.356012971 -0.216012971
40 9.005317998 0.009682002
41 8.885077981 -0.115077981
42 8.763905753 -0.008905753
43 8.854985458 0.090014542
44 9.003660203 0.001339797
45 8.839258915 0.205741085
46 9.228618924 -0.178618924
47 8.790904556 0.019095444
48 8.827759777 -0.267759777
49 8.265479467 0.179520533
50 8.701321012 0.088678988
51 8.808256089 0.156743911
52 9.008140237 0.056859763
53 8.932021315 0.072978685
54 8.962376252 0.052623748
55 9.124882297 0.065117703
56 9.348161769 -0.113161769
57 9.02965535 0.71534465
58 10.16187021 -0.731870214
59 8.795925992 -0.045925992
60 8.637130594 0.262869406
61 9.198533726 -0.158533726
62 9.00581336 0.02918664
63 8.846209727 -0.256209727
64 8.375771862 -0.040771862
65 7.962280825 0.152719175
66 8.134141268 0.005858732
67 7.951471287 0.108528713
68 8.304077379 0.035922621
69 8.24581044 -0.04081044
70 8.125995812 -0.110995812
71 7.960230364 -0.175230364
72 7.667455914 -0.037455914
73 7.601364167 -0.296364167
74 6.926407934 -0.006407934
75 6.863752002 0.091247998
76 7.07498417 0.04501583
77 7.090808324 -0.025808324
16
36 9.276155327 0.123844673
37 9.508305001 0.026694999
38 9.316284543 -0.016284543
39 9.356012971 -0.216012971
40 9.005317998 0.009682002
41 8.885077981 -0.115077981
42 8.763905753 -0.008905753
43 8.854985458 0.090014542
44 9.003660203 0.001339797
45 8.839258915 0.205741085
46 9.228618924 -0.178618924
47 8.790904556 0.019095444
48 8.827759777 -0.267759777
49 8.265479467 0.179520533
50 8.701321012 0.088678988
51 8.808256089 0.156743911
52 9.008140237 0.056859763
53 8.932021315 0.072978685
54 8.962376252 0.052623748
55 9.124882297 0.065117703
56 9.348161769 -0.113161769
57 9.02965535 0.71534465
58 10.16187021 -0.731870214
59 8.795925992 -0.045925992
60 8.637130594 0.262869406
61 9.198533726 -0.158533726
62 9.00581336 0.02918664
63 8.846209727 -0.256209727
64 8.375771862 -0.040771862
65 7.962280825 0.152719175
66 8.134141268 0.005858732
67 7.951471287 0.108528713
68 8.304077379 0.035922621
69 8.24581044 -0.04081044
70 8.125995812 -0.110995812
71 7.960230364 -0.175230364
72 7.667455914 -0.037455914
73 7.601364167 -0.296364167
74 6.926407934 -0.006407934
75 6.863752002 0.091247998
76 7.07498417 0.04501583
77 7.090808324 -0.025808324
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NEO CRYPTOCURRENCY
17
78 7.026071972 0.073928028
79 7.23316517 -0.13816517
80 7.036265735 -0.096265735
81 6.932928382 0.082071618
82 7.113534019 -0.093534019
83 7.054238079 -0.094238079
84 6.983716268 0.176283732
85 7.422744062 0.017255938
86 7.541531077 0.058468923
87 7.597069276 0.037930724
88 7.745700142 -0.095700142
89 7.583320545 0.061679455
90 7.708693427 -0.143693427
91 7.583088288 -0.023088288
92 7.590775098 0.269224902
93 8.081865637 -0.036865637
94 7.716910171 0.033089829
95 7.853223769 -0.138223769
96 7.739001452 0.010998548
97 7.62461452 0.14538548
98 7.966018321 -0.361018321
99 7.219100934 0.280899066
100 7.758445369 0.071554631
101 7.951033875 -0.001033875
102 7.965388264 0.629611736
103 9.20092389 0.26407611
104 9.176737316 -0.296737316
105 8.475899317 0.179100683
106 8.644860618 -0.414860618
107 7.851722923 -0.071722923
108 7.642515693 0.187484307
109 7.688026074 0.166973926
110 8.081806341 -0.146806341
111 7.873512811 -0.203512811
112 7.540039333 0.244960667
113 8.12489289 -0.05489289
114 7.974744863 0.055255137
115 7.981804069 -0.506804069
116 6.969095053 0.425904947
117 7.884905417 -0.154905417
118 7.697975822 0.182024178
119 8.482274841 -0.087274841
17
78 7.026071972 0.073928028
79 7.23316517 -0.13816517
80 7.036265735 -0.096265735
81 6.932928382 0.082071618
82 7.113534019 -0.093534019
83 7.054238079 -0.094238079
84 6.983716268 0.176283732
85 7.422744062 0.017255938
86 7.541531077 0.058468923
87 7.597069276 0.037930724
88 7.745700142 -0.095700142
89 7.583320545 0.061679455
90 7.708693427 -0.143693427
91 7.583088288 -0.023088288
92 7.590775098 0.269224902
93 8.081865637 -0.036865637
94 7.716910171 0.033089829
95 7.853223769 -0.138223769
96 7.739001452 0.010998548
97 7.62461452 0.14538548
98 7.966018321 -0.361018321
99 7.219100934 0.280899066
100 7.758445369 0.071554631
101 7.951033875 -0.001033875
102 7.965388264 0.629611736
103 9.20092389 0.26407611
104 9.176737316 -0.296737316
105 8.475899317 0.179100683
106 8.644860618 -0.414860618
107 7.851722923 -0.071722923
108 7.642515693 0.187484307
109 7.688026074 0.166973926
110 8.081806341 -0.146806341
111 7.873512811 -0.203512811
112 7.540039333 0.244960667
113 8.12489289 -0.05489289
114 7.974744863 0.055255137
115 7.981804069 -0.506804069
116 6.969095053 0.425904947
117 7.884905417 -0.154905417
118 7.697975822 0.182024178
119 8.482274841 -0.087274841
NEO CRYPTOCURRENCY
18
120 7.692309819 -0.112309819
121 7.102823976 -0.147823976
122 6.923705156 0.161294844
123 7.288812445 -0.203812445
124 6.709625698 0.315374302
125 6.81797571 -0.23297571
126 6.569916912 -0.364916912
127 5.716759188 0.098240812
128 5.654962343 -0.049962343
129 5.651705655 -0.006705655
130 5.728373607 0.126626393
131 6.055455878 0.014544122
132 5.85309608 0.14190392
133 6.121560808 0.133439192
134 6.408403488 0.001596512
135 6.045960563 0.064039437
136 6.071932781 -0.231932781
137 6.046434768 0.603565232
138 6.996241262 0.318758738
139 7.609547362 -0.094547362
140 7.357146931 0.277853069
141 7.962349884 0.237650116
142 8.186754803 -0.216754803
143 7.712929128 0.317070872
144 8.438064243 0.011935757
145 8.385446182 -0.395446182
146 7.261469177 -0.221469177
147 7.137159203 0.247840797
148 7.70862022 -0.36862022
149 7.484158385 0.540841615
150 8.547298879 -0.202298879
151 8.408939438 0.446060562
152 9.213484756 -0.213484756
153 8.948640195 0.326359805
154 10.17021062 1.164789376
155 12.60248148 -0.09248148
156 12.3858433 0.119156703
157 12.71021745 0.094782552
158 13.00953401 -0.099534008
159 13.52931348 0.555686523
160 15.39441196 0.140588038
161 15.79267894 0.052321064
18
120 7.692309819 -0.112309819
121 7.102823976 -0.147823976
122 6.923705156 0.161294844
123 7.288812445 -0.203812445
124 6.709625698 0.315374302
125 6.81797571 -0.23297571
126 6.569916912 -0.364916912
127 5.716759188 0.098240812
128 5.654962343 -0.049962343
129 5.651705655 -0.006705655
130 5.728373607 0.126626393
131 6.055455878 0.014544122
132 5.85309608 0.14190392
133 6.121560808 0.133439192
134 6.408403488 0.001596512
135 6.045960563 0.064039437
136 6.071932781 -0.231932781
137 6.046434768 0.603565232
138 6.996241262 0.318758738
139 7.609547362 -0.094547362
140 7.357146931 0.277853069
141 7.962349884 0.237650116
142 8.186754803 -0.216754803
143 7.712929128 0.317070872
144 8.438064243 0.011935757
145 8.385446182 -0.395446182
146 7.261469177 -0.221469177
147 7.137159203 0.247840797
148 7.70862022 -0.36862022
149 7.484158385 0.540841615
150 8.547298879 -0.202298879
151 8.408939438 0.446060562
152 9.213484756 -0.213484756
153 8.948640195 0.326359805
154 10.17021062 1.164789376
155 12.60248148 -0.09248148
156 12.3858433 0.119156703
157 12.71021745 0.094782552
158 13.00953401 -0.099534008
159 13.52931348 0.555686523
160 15.39441196 0.140588038
161 15.79267894 0.052321064
NEO CRYPTOCURRENCY
19
162 16.01029999 -0.23029999
163 15.99892653 0.116073472
164 15.96442673 0.195573273
165 16.31642979 0.203570208
166 16.75230445 0.212695554
167 16.94966984 -0.329669843
168 16.31476098 0.160239025
169 16.65169739 -0.306697391
170 16.00767901 0.032320993
171 16.18626709 -0.236267093
172 15.70853191 -0.208531912
173 15.32631828 -0.286318282
174 15.23505719 0.049942808
175 15.4230265 0.291973497
176 16.22756526 -0.097565258
177 16.06955301 0.095446991
178 16.23694943 0.04305057
179 16.55589557 0.034104428
180 16.75089085 -0.095890849
181 16.64694036 -0.031940361
182 16.76282276 -0.082822761
183 16.53164599 0.133354012
184 16.66998741 -0.089987414
185 16.50228715 -0.122287154
186 16.52986295 0.425137051
187 16.66688949 -0.106889494
188 16.42947582 -0.124475818
189 16.28877162 -0.05377162
190 15.6778579 0.252142095
191 15.78150648 0.01349352
192 15.64129831 0.023701689
193 15.52926675 1.26073325
194 18.22256951 -0.152569505
195 18.3035026 0.006497403
196 18.48051767 -0.100517673
197 18.09080795 -0.060807952
198 17.9124911 0.227508904
199 18.19151881 -0.181518814
200 17.93600067 0.193999334
201 17.97445659 0.145543406
202 18.52755464 -0.062554642
203 18.69642954 0.03857046
19
162 16.01029999 -0.23029999
163 15.99892653 0.116073472
164 15.96442673 0.195573273
165 16.31642979 0.203570208
166 16.75230445 0.212695554
167 16.94966984 -0.329669843
168 16.31476098 0.160239025
169 16.65169739 -0.306697391
170 16.00767901 0.032320993
171 16.18626709 -0.236267093
172 15.70853191 -0.208531912
173 15.32631828 -0.286318282
174 15.23505719 0.049942808
175 15.4230265 0.291973497
176 16.22756526 -0.097565258
177 16.06955301 0.095446991
178 16.23694943 0.04305057
179 16.55589557 0.034104428
180 16.75089085 -0.095890849
181 16.64694036 -0.031940361
182 16.76282276 -0.082822761
183 16.53164599 0.133354012
184 16.66998741 -0.089987414
185 16.50228715 -0.122287154
186 16.52986295 0.425137051
187 16.66688949 -0.106889494
188 16.42947582 -0.124475818
189 16.28877162 -0.05377162
190 15.6778579 0.252142095
191 15.78150648 0.01349352
192 15.64129831 0.023701689
193 15.52926675 1.26073325
194 18.22256951 -0.152569505
195 18.3035026 0.006497403
196 18.48051767 -0.100517673
197 18.09080795 -0.060807952
198 17.9124911 0.227508904
199 18.19151881 -0.181518814
200 17.93600067 0.193999334
201 17.97445659 0.145543406
202 18.52755464 -0.062554642
203 18.69642954 0.03857046
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NEO CRYPTOCURRENCY
20
204 18.93382375 -0.038823754
205 19.19220554 -0.337205538
206 19.26997596 0.320024042
207 19.01338754 -0.628387538
208 17.91499701 0.14500299
209 18.14728218 -0.317282184
210 18.50119432 0.388805675
211 19.54290607 -0.012906069
212 18.83025611 0.289743893
213 19.76752139 -0.717521388
214 18.29739959 -0.597399593
215 17.15588495 -0.210884945
216 17.04519019 -0.125190192
217 16.76484182 0.635158178
218 18.1267612 -0.2217612
219 18.1704433 -0.030443299
220 17.96753445 0.267465551
221 18.23669717 -0.051697166
222 17.6400606 -0.5300606
223 17.64095207 0.354047928
224 18.53266697 0.017333032
225 18.48600817 0.083991832
226 18.12908137 0.930918633
227 19.73448505 0.210514952
228 20.37620802 -0.951208023
229 19.69179833 2.503201675
230 24.25041955 -0.480419552
231 22.90208197 -0.597081972
232 22.0319263 0.298073701
233 22.55188405 -0.941884049
234 20.38052448 -0.615524476
235 19.7368781 -0.346878099
236 19.92304485 0.55695515
237 21.30911963 -0.609119632
238 20.63768172 -1.602681721
239 17.89000383 -0.415003835
240 17.82137347 0.10862653
241 17.82790417 -0.242904167
242 17.73468419 -0.634684192
243 16.53601187 1.208988135
244 17.83854196 -0.158541958
245 17.43312514 1.041874863
20
204 18.93382375 -0.038823754
205 19.19220554 -0.337205538
206 19.26997596 0.320024042
207 19.01338754 -0.628387538
208 17.91499701 0.14500299
209 18.14728218 -0.317282184
210 18.50119432 0.388805675
211 19.54290607 -0.012906069
212 18.83025611 0.289743893
213 19.76752139 -0.717521388
214 18.29739959 -0.597399593
215 17.15588495 -0.210884945
216 17.04519019 -0.125190192
217 16.76484182 0.635158178
218 18.1267612 -0.2217612
219 18.1704433 -0.030443299
220 17.96753445 0.267465551
221 18.23669717 -0.051697166
222 17.6400606 -0.5300606
223 17.64095207 0.354047928
224 18.53266697 0.017333032
225 18.48600817 0.083991832
226 18.12908137 0.930918633
227 19.73448505 0.210514952
228 20.37620802 -0.951208023
229 19.69179833 2.503201675
230 24.25041955 -0.480419552
231 22.90208197 -0.597081972
232 22.0319263 0.298073701
233 22.55188405 -0.941884049
234 20.38052448 -0.615524476
235 19.7368781 -0.346878099
236 19.92304485 0.55695515
237 21.30911963 -0.609119632
238 20.63768172 -1.602681721
239 17.89000383 -0.415003835
240 17.82137347 0.10862653
241 17.82790417 -0.242904167
242 17.73468419 -0.634684192
243 16.53601187 1.208988135
244 17.83854196 -0.158541958
245 17.43312514 1.041874863
NEO CRYPTOCURRENCY
21
246 19.54638034 -0.546380342
247 18.75851751 0.421482487
248 20.4868786 -2.156878596
249 16.22946158 0.225538417
250 15.89943053 0.725569466
251 16.08759546 -0.997595459
252 15.91479248 1.560207523
253 18.70626626 0.063733739
254 18.75216847 0.09283153
255 20.01077239 1.259227607
256 22.6194897 -0.509489703
257 21.86348539 1.411514612
258 25.25725653 1.092743472
259 26.28564714 0.834352859
260 27.51329292 -0.533292917
261 26.77672516 0.823274841
262 28.25189245 -0.476892454
263 28.59985559 0.550144414
264 29.95727502 -0.332275016
265 30.12573573 0.779264271
266 32.35518958 0.304810424
267 33.67969959 0.160300406
268 33.82774663 -0.527746631
269 33.55026593 -0.40526593
270 33.31481737 0.815182631
271 34.2615617 0.048438303
272 34.12283279 -0.717832786
273 32.25938273 1.070617271
274 33.35596231 0.484037689
275 34.38754509 -0.592545087
276 33.45829009 1.141709908
277 36.17063355 0.644366445
278 37.68181283 0.978187167
279 39.40949022 -1.519490219
280 37.15373793 -2.063737925
281 33.4820776 -0.402077601
282 32.69204753 -0.077047533
283 33.30527407 -0.370274066
284 31.84228725 0.492712755
285 33.98812323 -0.593123233
286 33.44745662 1.63754338
287 36.85241002 1.152589978
21
246 19.54638034 -0.546380342
247 18.75851751 0.421482487
248 20.4868786 -2.156878596
249 16.22946158 0.225538417
250 15.89943053 0.725569466
251 16.08759546 -0.997595459
252 15.91479248 1.560207523
253 18.70626626 0.063733739
254 18.75216847 0.09283153
255 20.01077239 1.259227607
256 22.6194897 -0.509489703
257 21.86348539 1.411514612
258 25.25725653 1.092743472
259 26.28564714 0.834352859
260 27.51329292 -0.533292917
261 26.77672516 0.823274841
262 28.25189245 -0.476892454
263 28.59985559 0.550144414
264 29.95727502 -0.332275016
265 30.12573573 0.779264271
266 32.35518958 0.304810424
267 33.67969959 0.160300406
268 33.82774663 -0.527746631
269 33.55026593 -0.40526593
270 33.31481737 0.815182631
271 34.2615617 0.048438303
272 34.12283279 -0.717832786
273 32.25938273 1.070617271
274 33.35596231 0.484037689
275 34.38754509 -0.592545087
276 33.45829009 1.141709908
277 36.17063355 0.644366445
278 37.68181283 0.978187167
279 39.40949022 -1.519490219
280 37.15373793 -2.063737925
281 33.4820776 -0.402077601
282 32.69204753 -0.077047533
283 33.30527407 -0.370274066
284 31.84228725 0.492712755
285 33.98812323 -0.593123233
286 33.44745662 1.63754338
287 36.85241002 1.152589978
NEO CRYPTOCURRENCY
22
288 39.20824702 1.096752984
289 39.42677263 -1.53177263
290 37.72627992 1.118720078
291 40.81984956 0.335150439
292 40.36523741 -1.620237413
293 36.17587051 0.734129485
294 36.05514434 -2.130144336
295 31.40519369 -0.720193694
296 30.7057376 0.069262402
297 29.70749511 -1.022495108
298 28.42913939 0.95086061
299 30.39481099 -0.299810985
300 30.37995612 0.600043877
301 31.7838775 -0.118877503
302 31.33865981 0.476340186
303 34.35694012 -0.436940116
304 33.34100113 1.788998868
305 37.93292934 0.637070663
306 39.02557322 -0.050573216
307 40.03235555 0.062644452
308 39.79608326 -0.881083257
309 38.85302306 -0.068023065
310 38.29292952 -0.297929525
311 38.34979342 1.220206583
312 40.94650925 -1.111509252
313 38.24109302 1.288906979
314 41.5881205 2.186879495
315 45.71280773 -1.122807727
316 45.81548648 2.049513523
317 51.21320214 1.056797864
318 52.71729227 0.23770773
319 53.94867897 0.136321034
320 54.05291646 -0.372916456
321 54.58421255 -1.064212551
322 53.56376388 1.291236121
323 56.55183579 0.27316421
324 56.90030562 -0.81530562
325 55.57852371 -1.058523706
326 53.05583829 -0.555838287
327 51.66570749 0.254292509
328 52.22861999 -1.533619994
329 48.37596114 2.13403886
22
288 39.20824702 1.096752984
289 39.42677263 -1.53177263
290 37.72627992 1.118720078
291 40.81984956 0.335150439
292 40.36523741 -1.620237413
293 36.17587051 0.734129485
294 36.05514434 -2.130144336
295 31.40519369 -0.720193694
296 30.7057376 0.069262402
297 29.70749511 -1.022495108
298 28.42913939 0.95086061
299 30.39481099 -0.299810985
300 30.37995612 0.600043877
301 31.7838775 -0.118877503
302 31.33865981 0.476340186
303 34.35694012 -0.436940116
304 33.34100113 1.788998868
305 37.93292934 0.637070663
306 39.02557322 -0.050573216
307 40.03235555 0.062644452
308 39.79608326 -0.881083257
309 38.85302306 -0.068023065
310 38.29292952 -0.297929525
311 38.34979342 1.220206583
312 40.94650925 -1.111509252
313 38.24109302 1.288906979
314 41.5881205 2.186879495
315 45.71280773 -1.122807727
316 45.81548648 2.049513523
317 51.21320214 1.056797864
318 52.71729227 0.23770773
319 53.94867897 0.136321034
320 54.05291646 -0.372916456
321 54.58421255 -1.064212551
322 53.56376388 1.291236121
323 56.55183579 0.27316421
324 56.90030562 -0.81530562
325 55.57852371 -1.058523706
326 53.05583829 -0.555838287
327 51.66570749 0.254292509
328 52.22861999 -1.533619994
329 48.37596114 2.13403886
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NEO CRYPTOCURRENCY
23
330 53.06235659 -0.947356586
331 52.38890342 0.546096579
332 53.15964717 0.975352829
333 54.88592847 -1.985928474
334 52.59145685 2.213543154
335 57.52069108 2.279308924
336 62.60817615 0.791823853
337 63.66276733 -2.402767325
338 59.31265434 0.082345664
339 59.82275925 -1.187759255
340 57.9614619 2.238538099
341 61.99825708 -0.373257081
342 63.40262855 2.53737145
343 66.62028762 -0.410287623
344 67.9210156 -1.696015598
345 64.90852202 -1.568522017
346 63.54374328 2.386256723
347 70.34435582 3.23064418
348 76.51632377 -1.461323773
349 77.26577787 1.289222132
350 79.48201141 0.562988588
351 83.75168935 0.578310646
352 84.56689114 0.548108861
353 84.46049932 0.669500677
354 88.02203799 -1.252037993
355 84.99422672 -0.879226718
356 84.83900983 -2.749009826
357 84.44365587 4.366344126
358 91.2440909 -6.689090896
359 76.92949025 -1.619490249
360 72.84070238 2.149297618
361 77.36914675 -3.84414675
362 71.53659747 4.268402534
363 83.19869221 -2.858692209
364 76.40727018 -0.682270178
365 73.93976816 1.160231839
23
330 53.06235659 -0.947356586
331 52.38890342 0.546096579
332 53.15964717 0.975352829
333 54.88592847 -1.985928474
334 52.59145685 2.213543154
335 57.52069108 2.279308924
336 62.60817615 0.791823853
337 63.66276733 -2.402767325
338 59.31265434 0.082345664
339 59.82275925 -1.187759255
340 57.9614619 2.238538099
341 61.99825708 -0.373257081
342 63.40262855 2.53737145
343 66.62028762 -0.410287623
344 67.9210156 -1.696015598
345 64.90852202 -1.568522017
346 63.54374328 2.386256723
347 70.34435582 3.23064418
348 76.51632377 -1.461323773
349 77.26577787 1.289222132
350 79.48201141 0.562988588
351 83.75168935 0.578310646
352 84.56689114 0.548108861
353 84.46049932 0.669500677
354 88.02203799 -1.252037993
355 84.99422672 -0.879226718
356 84.83900983 -2.749009826
357 84.44365587 4.366344126
358 91.2440909 -6.689090896
359 76.92949025 -1.619490249
360 72.84070238 2.149297618
361 77.36914675 -3.84414675
362 71.53659747 4.268402534
363 83.19869221 -2.858692209
364 76.40727018 -0.682270178
365 73.93976816 1.160231839
NEO CRYPTOCURRENCY
24
Regression Plots
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Normal Probability Plot
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Circulation Line Fit Plot
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24
Regression Plots
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Circulation Line Fit Plot
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NEO CRYPTOCURRENCY
25
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Volume Line Fit Plot
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25
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Volume Line Fit Plot
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1 out of 25
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